1772 search results - page 290 / 355 » Classifying Problems into Complexity Classes |
106
Voted
EUROCAST
2007
Springer
15 years 6 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
188
Voted
Publication
In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex
scenes using a monocular, potentially moving, uncalibrated ca...
ICCV
2007
IEEE
16 years 2 months ago
2007
IEEE
For many multi-part object classes, the set of parts can vary not only in location but also in type. For example, player formations in American football involve various subsets of...
112
Voted
KDD
2009
ACM
16 years 1 months ago
2009
ACM
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
108
Voted
MLDM
2007
Springer
15 years 6 months ago
2007
Springer
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...